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Record W2892293112 · doi:10.2106/jbjs.17.01405

The Impact of Common Urologic Complications on the Risk of a Periprosthetic Joint Infection

2018· article· en· W2892293112 on OpenAlexaff
Nahid Punjani, Brent A. Lanting, J. Andrew McClure, Jennifer Winick‐Ng, Blayne Welk

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsInstitute for Clinical Evaluative SciencesWestern University
Fundersnot available
KeywordsMedicinePeriprostheticInterquartile rangeUrinary systemJoint arthroplastyRetrospective cohort studyArthroplastyEmergency departmentCohortInternal medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Periprosthetic infections after total hip arthroplasty (THA) or total knee arthroplasty (TKA) are substantial complications, and there are conflicting reports of their association with urologic complications. Our objective was to determine whether urinary tract infection (UTI) and acute urinary retention (AUR) are significant risk factors for joint infections after THA or TKA. METHODS: We performed a population-based, retrospective cohort study of patients who were ≥66 years old when they underwent an initial THA or TKA between April 2003 and March 2013. Investigated exposures included a UTI presenting for treatment within 2 years after joint replacement, as well as AUR within 30 days after THA or TKA. The primary outcome was joint infection requiring hospital admission following THA or TKA (which had to occur within 2.25 years after THA or TKA for the UTI exposure or 120 days for the AUR exposure). RESULTS: A total of 113,061 patients met the inclusion criteria and had arthroplasties (44,495 THAs and 68,566 TKAs) during the study period. The median age was 74 years (interquartile range [IQR], 70 to 79 years). Of those patients, 28,256 (25.0%) had at least 1 UTI and they were more likely to be older and female; to have had previous antibiotic exposure, cystoscopy, or urinary retention; and to have atrial fibrillation. Most of those UTIs were coded as nonspecific UTI, and the patient was seen for outpatient treatment in a non-emergency department setting. A total of 2,516 patients (2.2%) had AUR within 30 days of the procedure. Those patients were more likely to be older and male, to have medical comorbidities, to have had previous transurethral procedures or cystoscopy and previous urology visits, and to have received a general anesthetic during their procedure. A total of 1,262 patients (1.1%) had joint infection requiring hospital admission. In multivariate Cox regression analysis, UTI was associated with an increased risk of joint infection (hazard ratio [HR], 1.21 [95% confidence interval (CI), 1.14 to 1.28]; p < 0.01). However multivariate analysis did not demonstrate an association between AUR and joint infection (HR, 0.99 [95% CI, 0.60 to 1.64]; p = 0.98). CONCLUSIONS: UTI was associated with increased risk of hip or knee periprosthetic joint infection, whereas AUR was not a significant risk factor. Timely and appropriate treatment of symptomatic UTIs in this patient population may be important to prevent periprosthetic joint infection. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.295
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2018
Admission routes1
Has abstractyes

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